Automatic speech recognition (ASR) can be used to score oral reading fuency (ORF) assessments to ameliorate current inadequacies (e.g., administration errors, high opportunity cost), and represents an important part of a larger solution to improve traditional ORF. But more research is needed on how ASR performs for diverse student groups. The purpose of this study is to examine the accuracy of ORF scores as generated by ASR compared to humans, and in particular, differential effects for students with disabilities (SWD) and those receiving English language (EL) supports. Across Grades 2 to 4, the ORF word score agreement rates between human criterion and ASR were significantly lower for SWDs compared to their non-SWD/non-EL peers, but the differences in ORF WCPM scores between human and ASR were not exacerbated for SWD or EL students. We speculate that the ASR may be less accurate than a human scorer for SWDs at the word level, but the difference in scoring is mitigated when scores are aggregated at the passage level.